University of Surrey

UKRI Gateway to Research · FY 2026 · 2026-09

The James Webb Space Telescope (JWST) recently discovered very young galaxies - which existed shortly after the Universe began - whose chemical compositions are dramatically different from both today's galaxies, and from the expectations of astrophysicists. In these “JWST galaxies”, nitrogen is enhanced by a approximately factor of ten compared to similar galaxies nearby and, in some cases, carbon also appears enhanced. These unexpected chemical signatures challenge our models of stellar evolution and galactic-chemical evolution, which had not predicted such rapid and substantial production of these elements in the early Universe.   The project addresses this gap by extending our existing stellar- and galactic-chemical evolution framework to model both single and binary stars at zero to solar metallicity. The ultimate goal is to determine which types of stars make the chemical elements in the first galaxies. To achieve this, we will incorporate state-of-the-art stellar-population results into hydrodynamic galactic chemical evolution (GCE) models. Our approach leverages the binary_c population nucleosynthesis code, led by Dr Robert Izzard, which simulates stellar evolution and nucleosynthesis in just a few seconds per star. This speed is essential for investigating large populations and exploring variations in uncertain input physics, such as mass-loss rates.   The proposal is structured around three main work packages. Work Package 1 updates our stellar-model database using the MESA stellar-evolution code. This effort includes training personnel to use our binary_c framework with its new MINT interpolator, updating grid-generation software with the latest stellar input physics, and ensuring nuclear-reaction rates are consistent between MESA and binary_c. Since MESA struggles with supernova yield calculations, Prof. Chiaki Kobayashi (CK) will provide these yields, which will be incorporated into our system and stored in a standard GCE-ensemble format. These improved yields, which extend up to stellar masses of 1000 M?, will allow us to explore various initial mass functions in later work. Colleagues from the BRIDGCE consortium (bridgce.ac.uk) will assist to ensure our input stellar and nuclear physics are state-of-the-art.   Work Package 2 applies the WP1 data to binary stars, interactions in which, such as mass transfer and mergers, greatly affect chemical yields. This will be the first systematic exploration of nucleosynthesis in zero-metallicity binary populations, so breaks very new scientific ground. We will also use binary_c’s latest machine-learning algorithms to speed up our science, ready for the incoming AI revolution. Work Package 3 then integrates our results into GCE simulations. We will run both one- and three-dimensional hydrodynamic simulations, sampling star-formation histories from cosmological models. These simulations will be compared statistically with the ensemble properties of galaxies observed by JWST and other upcoming surveys such as DESI and PFS. By accounting for detection limits and selection effects – using published stellar spectral-synthesis data to mimic nebular emission – we aim to identify the sources of both chemical enrichment and ionisation in the early Universe.   This multidisciplinary project aligns with several key STFC science challenges, including understanding the formation of the initial structure of the Universe, the birth and evolution of the first stars and galaxies, and the nuclear processes that create chemical elements. With collaborative support from the BRIDGCE consortium, and based on our existing and well-tested stellar-evolution and GCE software and expertise, our approach is innovative and relatively low risk, and aims to solve key problems in astronomy with implications for stellar, galactic and cosmological astrophysics.    

UKRI Gateway to Research · FY 2026 · 2026-09

We will develop and apply new techniques in quantum field theory (QFT), analyse gravitational systems, and investigate the fascinating relationship between these two scientific areas. Quantum theory revolutionized physics and powers modern technologies, and its unification with Einstein’s foundational idea of spacetime yields QFT. We will focus on QFT as a powerful computational tool to address fundamental problems in low-dimensional physics, in perturbative QFT, and in the theory of open quantum systems in the presence of a thermal environment. Our team has a consolidated and unique expertise in these areas, and a strong synergy to tackle the proposed research problems. Firstly, we will understand unconventional spin chains which have large number of symmetries, viewed as an exactly solvable laboratory to model realistic physical systems. Secondly, we will derive powerful methods to organise perturbative QFT by recasting the latter into the modern mathematical language of homotopical algebra. This will have far-reaching ramifications for the efficient study of collider physics. Thirdly, we will use phase transitions---analogous to the change of states of matter from e.g. a solid to a gas---as a tool to reveal the nature of the quantum-classical transition in quantum systems in contact with a thermal bath. These challenges are at the core of the agenda which involves mathematical methods applied to urgent problems in quantum theory and high-energy physics. We are particularly excited to use novel applications of QFT methods to the vast area of open quantum systems. Besides QFT, another centre piece of our research is Einstein’s theory of gravity and its supersymmetric extensions. In particular, we will investigate symmetries and algebraic structures in black hole solutions of gravity. Firstly, we will analyse the geometry and symmetries near to the event horizon of black holes in various dimensions. Secondly, we will analyze the deformation theory of black holes through the modern lens of homological perturbation theory thus providing valuable new insights into the nature of black holes. Addressing these problems is of particular topical importance because of recent constructions of novel black holes exhibiting non-uniqueness. Our group has developed significant expertise in classifying geometric structures associated with black holes as well as in homotopical algebras in field theories. We are thus in a unique position to exploit years of innovation and development of the necessary techniques in order to solve these problems.  

UKRI Gateway to Research · FY 2026 · 2026-04

Revolutionary Lovers: One Century of Anarchist Sexual Politics in Global Perspective (1870-1970) Anarchists have been a vanguard in challenging many aspects of gendered norms, sexual behaviour and the very concept of love since the late nineteenth century - while simultaneously reinforcing others, such as ideas of naturalness and heterosexuality. This project examines the interplay between love and politics in anarchist discourse and praxes in the nineteenth and twentieth centuries, from the emergence of a self-identified anarchist movement in the early 1870s, to the mid-twentieth century, on a global scale. It develops the first in-depth transnational analysis of how revolutionary love and sexuality have shaped the personal and life experiences of politically engaged individuals, as well as broader social debates on intimacy and its political meanings. By exploring the achievements and the failures of the anarchist movement through histories of transformative love practices and ‘revolutionary lovers’, the project critically assesses anarchist doctrines and praxes in the past and their relevance today. It will foreground anarchism’s unique role in theorising the articulation between individual and collective emancipation, and set out a research agenda that confronts theories and practices, documents unheeded and silenced histories, and analyses the interconnections between the deeply personal and the political, contributing to a lively strand of radical history. Revolutionary Lovers therefore makes conceptual and empirical contributions to the history of anarchism, and to the wider social and cultural histories of gender, sexuality and love. The global circulation of anarchist ideas and practices of sex and love remains largely unrecognised and lacks sustained and systematic analysis. This project embraces this challenge and opens up new research questions in emphasising the intertwining of the personal, political and global dimensions of anarchist sexual politics, and restoring the anarchists’ sophisticated levels of criticism and reflection about the linkages between sex, gender, love and political repression and liberation. It probes intimacies within and between different world regions and charts new geographical and emotional venues where love and intimacy were configured. It will establish an international specialist network of five core participants, defining objectives to be taken up subsequently by a larger research team and community. The project combines chronological and thematic approaches: each member of the core team will deliver a case study exploring revolutionary lovers and highlighting key ideas, moments, actors and sites in redefining romantic and sexual concepts. Each case study speaks to the three overarching strands, which foreground the core impact areas of these anarchist praxes and theories of love: Family/State; Production/Reproduction; and Nature/Science. A concluding conference will present and broaden the project’s findings, drawing on Asia, Europe and the Americas for its case studies, with contributions on India, Northern Africa and Latin America for the conference. Based on the expertise of the Project Lead (Professor Richard Cleminson, University of Leeds) and an international core team of researchers in the study of transnational anarchism and histories of radical intimacies, and using the couple as the unit of analysis, the project will shed new light on how anarchists experienced and reconceptualised sexual politics.  

UKRI Gateway to Research · FY 2026 · 2026-03

On November 11th 2025, the level of ionising radiation in the atmosphere, recorded at ground level, suddenly increased; at Lerwick, radiation levels doubled in 10 minutes. Such an increase is called a Ground Level Enhancement (GLE), and the event in question, denoted GLE 77, was the largest in almost 20 years. GLEs are caused by space weather events, specifically by high energy protons  accelerated at the Sun during solar flares and coronal mass ejections. Travelling close to the speed of light, on reaching the Earth they interact with Earth’s atmosphere creating cascades of subatomic particles including protons, neutrons, and muons. While such cascades are always present due to galactic cosmic rays, their number can increase by orders of magnitude during a GLE. Such events are a particular hazard for aviation since they increase the radiation dose received by passengers and crew as well as increasing the risk of malfunctions in safety-critical on-board electronic flight control units. This risk was recently highlighted by the grounding of around 6000 Airbus A320s following the discovery of vulnerabilities to “intense solar radiation” in the avionics. Other critical infrastructure at ground level, including nuclear power controls and autonomous vehicles, can be affected in similar ways. The great complicating factor of GLEs is their anisotropy. That is to say that their intensity varies significantly with location on Earth. This can result in localised radiation hotspots, the scale of which is not fully understood. Measuring atmospheric radiation levels is therefore critical to mitigating the risk associated with GLEs. They have been observed in the ground-level neutron monitor network since 1949, but this is geographically sparse and has declined to around 50 monitors worldwide. The consequence of this combination of a highly anisotropic phenomenon and a sparse observation network is that, during any given GLE, there is great uncertainty as to the true severity of the event and the risk it presents. A denser network is required to unravel GLE’s detailed characteristics. Recent research has identified that existing networks of neutron detectors used for soil moisture measurements, called Cosmic Ray Neutron Sensor (CRNS) networks, could be used to observe GLEs in unprecedented spatial resolution (there are over 40 CRNS sensors in the UK alone). This research reached positive conclusions about the potential of CRNS networks for GLE detection, but the absence at that time of a large enough GLE since the inception of such observations (2008) meant there was a lack of any practical demonstration of its efficacy. GLE 77 is the first observable event for CRNS networks, and provisional data from the UK, USA, Germany, and Australia shows that it was very widely registered. The project has two principal aims:  To collect as much data as possible during and around GLE 77 from CRNS networks globally.  To analyse the resulting data set in order to study GLE anisotropy in unprecedented spatial resolution. Urgently achieving these aims is necessary in order to preserve extremely valuable data which may otherwise be lost. Furthermore, a deeper understanding of GLE 77 and any risks which may have been missed due to relying on neutron monitors alone is of vital importance and is urgently required.

UKRI Gateway to Research · FY 2026 · 2026-03

Context It is estimated that 25% of the world has latent tuberculosis, and in 2023 alone, there were more than 11 million tuberculosis cases and 1.3 million deaths, making the causative agent, Mycobacterium tuberculosis the leading cause of infectious disease world-wide. New treatments are desperately needed to increase the effectiveness of current tuberculosis treatments and to combat a rise in antibiotic-resistant strains of M. tuberculosis.   Challenge M. tuberculosis has the remarkable ability to cause both acute life-threatening diseases and symptomless latent infections that can last a lifetime. A key to understanding the tuberculosis disease process is M. tuberculosis’ remarkable metabolic flexibility and plasticity that enables it to consume a wide range of human host-derived nutrients. A fundamental and currently unanswered question is how pathogens such as M. tuberculosis coordinate their metabolism to produce the cellular components that cause disease. Answering this question is of therapeutic significance as targeted dysregulation would both starve the bacteria and prevent it from successfully colonizing the human host, effectively killing the bacteria and stalling the disease process.   Timeliness We have discovered a unique regulatory protein that is required for M. tuberculosis to consume energy sources essential for its survival in the host and for its ability to cause disease.  We have shown that without this protein M. tuberculosis cannot grow in human cells or cause tuberculosis disease in a mouse.  Our hypothesis is that this regulatory protein that we have named Virulence Associated Dikinase (VadK), coordinates metabolism and virulence by interacting with protein partners.  This project will test this hypothesis by capitalizing on our combined expertise and novel experimental tools in microbiology, biochemistry, and structural biology.   Aims and Objectives Our overall objective is to find out exactly how this unique regulatory system works.   Exploiting our strong, complementary, and multi-disciplinary expertise we will decipher: The physical determinants of VadK's interactions with its partner proteins How VadK and partner proteins control metabolism and hence the production of genes required to cause tuberculosis. The effect of modulating the VadK system on metabolism and survival during experimental infection.   Through this research, we will start to understand the fundamental biology of how M. tuberculosis coordinates metabolism to cause disease.   Benefits Through this research we will discover how pathogens link metabolism with virulence that will be of benefit to scientists studying how cells coordinate these activities. We have also identified this system in other clinically and industrially relevant bacteria and this research will guide and inspire future studies in this area. The biology from this project will identify and validate drug targets that can be leveraged by the pharmaceutical industry and charities that are so urgently looking for new approaches to treat tuberculosis. Therefore, this work fits firmly into the MRC remit of understanding human infectious diseases which focuses on tackling global infectious diseases, including tuberculosis, and translating these findings to benefit human health.

UKRI Gateway to Research · FY 2026 · 2026-03

Communication technologies in the United Kingdom and abroad have advanced substantially over the last two decades to enable individuals to gain Internet access at home, work, in public spaces as well as on the move. This growth in accessibility and also consumer demand has driven the need to extend Internet availability ubiquitously to enable consistent connectivity, especially in locations where usage is high. One of these locations is on board trains, which may carry up to 3000 passengers at a time, the majority of whom are in need of high speed data communications while on the move yet at the present time such provisions are minimal. The reason for poor Internet access on board trains is partly due to economic limitations in deploying trackside base stations or access points to deliver the necessary connectivity to provide WiFi, cellular communication and other services. However, to date there does not exist a suitable technology to deliver high speed Internet connectivity to trains, especially within tunnels, thereby limiting access for existing rail networks with substantial tunnel lengths (e.g. underground networks) but also future mass-transit technologies extensively using tunnels, such as hyperloops. Internet connectivity on trains has substantial importance to society (to meet passenger demands on board trains), economy (as Internet connectivity is crucial to business productivity with personnel working on the move) and environment (where Internet connectivity helps in making rail-based transport a preferred option), thus proving the transformative impact potential of this research. This project will provide a low cost, low energy, solution with ease of implementation to meet the need to deliver gigabit wireless connectivity to rail-based transport, especially in tunnels, in order to enable them to provide the required on board wireless services. To achieve this, the project will build on the seminal work recently developed and published by the research team in the Royal society Proceedings, which outlines their new transmission concept known as, Linear Angular Momentum Multiplexing (LAMM). In order to reach the technology readiness level that could enable development trials beyond the project to deliver the necessary connectivity to rail services in existing tunnels for rail networks, this concept needs to be further developed for 3-dimentional environments, i.e. Three Dimensional Angular Momentum Multiplexing (3DAMM), and this project will carry out the necessary foundational science work to do so. Two major areas of research are required to reach this point. First it is necessary to determine the optimum antenna topology and radio configuration for 3DAMM, which will use a substantially different wireless communication channel to that used in conventional mobile communications. Secondly, it will be necessary to pioneer new antenna solutions for 3DAMM that are both in their design and operation significantly different from conventional antennas in order to function on trains, especially when they are in tunnels. These two areas of research interrelate in terms of how the wireless radio will propagate, especially within the tunnel, which needs to be modelled appropriately so that the concept can be optimised. Therefore, the project is based within the area of radio frequency and microwave devices as well as the associated radio communication system. Finally, the work will form a proof of concept using appropriate demonstrator platforms to show the ability of 3DAMM to deliver the communication requirements for rail-based transport moving at high speed.

UKRI Gateway to Research · FY 2026 · 2026-02

Biological cells generate forces that drive various functions, including intracellular processes such as division and transport, as well as responses to extracellular stimuli such as cell polarization and migration. These processes are accomplished via structural changes in the cytoskeleton resulting in cell shape changes. The forces behind these deformations originate from interactions between cytoskeletal components, namely biopolymers and motor-proteins. Mechanical stimulation from the extracellular environment also influence these interactions, leading to remodelling of cellular morphology. Thus, the cytoskeleton is an adaptive and active material, which uses chemical energy at the nanoscale giving rise to active behaviour at cellular length scale. Currently, interactions between individual cytoskeletal biopolymer and motor-proteins at the nanoscale are relatively well-known. However, experimental characterization of the forces that these components collectively generate and how they can shape cells remains a significant challenge blocking fundamental progress in biology and innovation in materials science. The aim of this research is to understand how the evolution of cellular forces within the intracellular space, from the molecular length scale to the entire cell, leads to changes in cell structure and regulation of morphology. This will be achieved by developing an innovative experimental platform to tackle these fundamental questions. I will engineer a 3D system made of biopolymers and motor-proteins able to mimic the functionality of the cytoskeleton. This bioinspired experimental setup allows us to investigate in a controlled manner how living matter respond to mechanical external stimuli at different length scales and accomplish shape changes. I will employ microfluidics, photo-switchable proteins, and fluorescence microscopy to achieve the following objectives: Understanding the effects of geometry on the self-organisation of 3D bioinspired systems and how the external environment couples with the active network activity. How? By assembling active networks made of microtubules and motor-proteins and enclose them within confinements of varying nature and size, from compartments with solid walls to vesicles with deformable membranes. Unravelling activity at different length scales (from few microtubules and motor-proteins to the interconnected network) and studying how this activity is transferred across these length scales. How? By integrating photo-switchable motor-proteins to locally activate by light defined portions of the active networks. Studying the mechanisms of how cellular active networks collectively change their symmetric morphology to a tapered shape, aka symmetry-breaking. How? By encapsulating and anchoring active networks within cell-like membranes, and locally triggering network activity using light. The proposed project has interdisciplinary scope with relevance for scientists interested in understanding the physics of life. In the UK the growing interest in this topic led to the foundation of the scientific network Physics of Life, which includes researchers in physical and biological sciences. The successful assembly of these active self-organising structures would be a significant milestone for novel model systems that will enable us to understand the physical forces in the cytoskeleton. By considering the collective forces generated by biopolymers and motor-proteins involved in cellular processes, we can unlock new investigation avenues into cellular diseases. Processes such as metastasis and wound healing are based on force generation at different length scales and cellular deformation leading to migration. The new insights offered by this proposal may lead to novel medical research that address physical forces for the development of new therapeutic procedures.

UKRI Gateway to Research · FY 2026 · 2026-02

This fellowship aims to integrate community-level smart data with longitudinal cohort data to improve how England anticipates and plans for the health and care needs of its ageing population. As more people live longer at home, often with multiple long-term conditions, their experiences are shaped not only by health but also by where they live. Different communities face distinct risks and opportunities in ageing, access to services, housing, and transport. This project addresses the challenge of forecasting diverse, place-specific needs over time. The work will combine smart data from the Ageing in Place Classification (AiPC), a geodemographic measure of older people’s neighbourhood contexts, with place-based longitudinal data resources. These datasets will be integrated at the lower super output area (LSOA) level with the English Longitudinal Study of Ageing (ELSA), which provides rich information on health, wellbeing, care, and living environments since 2002. Together, they will enable testing of AiPC’s explanatory power for health outcomes and its potential for predictive modelling. Using this combined data, ELSA participants will be matched to specific neighbourhood profiles enhanced with longitudinal indicators. Analyses will assess how well AiPC captures differences in health trajectories and whether individual outcomes align with the characteristics of their neighbourhood profile. A measure of “closeness of fit” will be developed to show whether individuals whose circumstances match their neighbourhood type experience different outcomes compared with those in “misfit” contexts. If alignment is weak, the project will still generate customised longitudinal profiles of changes in health states, such as functional decline, multimorbidity, or care dependency, at the LSOA level. These will be summarised for local authorities and shared with decision-makers as open reports, directly informing short- and medium-term planning. If alignment is strong, the predictive power of neighbourhood profiles can be quantified, producing probabilities of transitions between health states over time. These probabilities can then be integrated into the English Future Elderly Model (E-FEM), a microsimulation platform developed for England, which until now has lacked the granularity to forecast at neighbourhood scale. This research will address major gaps in current modelling, where national or regional forecasts can mask local inequalities. By embedding neighbourhood-sensitive logic into microsimulation, the project will provide the first fine-grained forecasts of ageing outcomes across England’s diverse communities. Aim: To assess and exploit the value of AiPC for understanding and forecasting ageing outcomes in England. Objectives: 1a. Operationalise “closeness of fit” between participants and neighbourhood profiles; test whether fit/misfit moderates longitudinal transitions. 1b. Evaluate whether neighbourhood profile adds predictive power to models of ageing outcomes beyond individual predictors. 2a. Produce customised longitudinal profiles of health changes at local authority levels for local planning. 2b. Compare changes across AiPC groups in ELSA; test transition probabilities for integration into E-FEM. By generating comprehensive longitudinal profiles at low-level geographies, this project will help identify where resources are most needed and inform sustainable service planning. Bridging geography, health data science, and simulation, it offers an innovative approach to support older people to live healthier, more independent lives in the places they call home.

UKRI Gateway to Research · FY 2026 · 2026-01

The i-MOBYL project aims to identify, co-create, and implement inclusive, evidence-based, and acceptable design and policy interventions that empower young adolescents (YA), aged 11-15, across diverse European contexts to engage in out-of-home activities using active and multimodal travel, within the framework of 15-minute cities (15mC) and focusing on equity and health outcomes. i-MOBYL advances the state of the art by addressing key scientific and societal gaps: the underrepresentation of YA and lack of community engagement in mobility planning; the absence of co-created operationalizbehavied visions; limited empirical evidence on YA activity patterns and travel behavior; a lack of tailored, validated interventions grounded in behaviour change theory; limited implementation due to weak local authority involvement and high resource demands; insufficient insight into intervention performance; and absent mechanisms to scale YA-focused mobility planning to different stakeholders. Following a strategic planning cycle through seven interlinked work packages across five countries, i-MOBYL will deliver: co-created visions with YA, operationalized into KPIs (WP2); a multinational empirical evidence base detailing YA’s full range of activity and mobility patterns across diverse urban settings (WP3); validated, co-designed interventions promoting YA’s active and multimodal travel grounded in behavior change theory (WP4); replicable guidelines for community engagement and intervention delivery (WP5); a co-created framework to assess interventions regarding acceptability, practicability, effectiveness, affordability, side-effects, equity (APEASE criteria) and anticipated health outcomes (WP6); and tailored knowledge transfer material disseminated via the DUT knowledge hub, established European networks, and professional and academic outlets (WP7). All outputs are developed with active involvement from YAs of diverse backgrounds in the five partner cities. These include: i) the evidence base cities Eindhoven (NL) and Basel (CH) which will contribute to building the empirical foundation on YA activity and mobility patterns, with YA participating through schools and youth centres; and ii) the Living Labs (LLs) Paris (FR), Guildford (UK), and Salzburg (AT), which will serve as transdisciplinary test beds for intervention co-design and implementing with YA, SMEs, urban authorities and civil society actors. i-MOBYL employs a mixed-methods, interdisciplinary, and participatory approach, integrating transport studies, urban planning and design, behavioral science, co-design and public health. Drawing on social-ecological and COM-B theoretical models, i-MOBYL applies systems-thinking to analyse how YA’s physical, social, and digital environments shape their mobility choices. While taking a systemic perspective, i-MOBYL acts locally, with bottom-up community engagement as a key driver of behavior change. Equity is emphasized by focusing on the distinct needs of YA, an underrepresented group in urban mobility planning, and applying an intersectional lens that accounts for gender, socio-economic, and cultural dimensions. The project benefits from the complementary research strengths of academic partners conducting cutting-edge research across disciplines. Community engagement, including strong partnerships with local stakeholders in the three LLs, will directly support research activities, amplify local impact, and enable cross-sectoral and cross-national knowledge transfer. i-MOBYL’s results will be highly usable as it directly aligns with societal needs, reflects the diversity of YA and urban contexts, and spans the full innovation pipeline from academic research to civil society, public authorities, and SMEs. By advancing the scientific state of the art and translating findings into actionable strategies, i-MOBYL aims to inspire lasting behavior change towards sustainable travel, starting with Europe’s young adolescents.    

UKRI Gateway to Research · FY 2026 · 2026-01

My proposed research programme will address two fundamental questions in astrophysics: how do galaxies evolve and what is the nature of the ubiquitous yet invisible substance known as dark matter? We know that galaxies began as tiny quantum fluctuations in the early Universe, which then expanded with inflation to produce local overdensities in dark matter. These clumps attracted gas, which condensed to form the first stars. As these stars clustered they formed galaxies. What we do not yet know, however, is how these early featureless groups metamorphosed into the diverse range of morphologies that can be observed today. Galaxies in our night sky contain anything from a hundred million to a hundred trillion stars and whilst many are elliptical, or spheroidal in shape, others are more exotic; like our Milky Way, which resembles a pancake with spiral arms. The evolution of galaxies has a number of drivers acting on different scales. The interstellar scale includes processes such as star formation, explosions of massive stars, and interactions between stars. On a larger scale, mergers between nearby galaxies serve to reshape the distribution of stars as well as deposit alien stars from satellite galaxies in the outer haloes. The haloes of dark matter that enshroud all galaxies modulate the rate of star formation and merger events. We need to reveal the detailed balance between these drivers of galactic evolution to explain the origin of the present diversity. The emerging field of 'galactic archaeology' offers an extremely promising path to answering these questions. It relies on the concept of 'descent with modification' in evolutionary biology, which describes the passing down of traits between generations. All stars fuse new elements in their cores. The most massive stars live short lives, perishing in cataclysmic explosions that expel these elements into the surrounding gas. The gas condenses to form the next generation of stars. Thus, the chemical patterns of stars function as 'stellar DNA', betraying the state of chemical enrichment of the gas at the time and place of birth. Furthermore, the positions and velocities of stars indicate their orbits, which in turn reflect the distribution of dark matter in the galaxy. Thanks to the unprecedented success of recent surveys there has been a revolution in the stellar data available for the Milky Way and other nearby galaxies. I will establish a new research field, carrying out detailed galactic archaeology studies of the Milky Way and extending these to a large number of nearby galaxies. My interdisciplinary background in astrophysics and engineering will uniquely enable me to integrate advanced statistical tools with new state-of-the-art galaxy models, thus enabling me to fit a plethora of data, whilst tackling calibration issues. These tools will have far-reaching implications throughout a number of fields, including astrophysics, engineering, and health sciences, where I have already generated notable impact. My models will describe the distribution of dark matter throughout these galaxies and unlock the role played by star formation, chemical enrichment, interactions between stars, and mergers with nearby galaxies. This will place new and exciting limits on our field’s remaining unknowns such as the size of the Universe's smallest galaxies. The project will thus address central questions of astrophysics, whilst in parallel feeding back into the Big Data revolution back on Earth.

UKRI Gateway to Research · FY 2025 · 2025-12

Generative artificial intelligence (GenAI) is a machine learning model that mimics human language and, by using probability, generates content across a range of formats. GenAI is disrupting numerous industries, including academia. It can be used across the entire research pipeline, from ideation and literature review to data analysis and manuscript preparation; it is easily accessible, deployable, and offers productivity gains to researchers. However, this raises questions about its implications for research integrity, especially if GenAI is used to substitute specialist technical expertise such as statistical methodology or data interpretation. This tension between achieving productivity gains and maintaining research integrity is particularly significant in healthcare research where methodological and design errors and misinterpretation of data can severely impact health outcomes and quality of life. Security, rigor, accuracy and robustness are all vital components to health research as findings may directly impact patient outcomes, inform clinical guidelines, and shape future research funding. Methodological errors, no matter the cause, in this domain can damage the credibility of research in the eyes of the public if these errors lead to the publication of misleading information and changing recommendations. Healthcare researchers minimise these errors by working in multidisciplinary teams, with individuals of various specialised backgrounds. Insights from clinical, statistical, behavioural science, and economics backgrounds are combined to develop hypotheses and analyses that better detect, quantify and interpret the complex relationships between variables ensuring high quality methodology, more impactful conclusions, and limiting downstream consequences. GenAI can improve access to specialised knowledge, allowing researchers to engage in complex methodologies outside their speciality (e.g., generating data analysis code for non-statistical researchers). This offers enormous benefits, allowing researchers to pursue complex and robust methodologies, however the potential costs of this approach are unclear. Information generated by GenAI reflects the most probable response given the data it was trained on, not specialised knowledge of a topic. The initial answers generated by GenAI can be incorrect or misinterpreted by individuals with limited expertise, resulting in a form of epistemic, or knowledge, trespassing where researchers make judgements outside their core domain. Epistemic trespassing may inadvertently introduce subtle but consequential errors. This research programme proposes to explore how GenAI is used outside one’s specialty within healthcare research. Findings aim to inform recommendations and an initial evidence-based framework on effective GenAI use. Initially, a survey will be administered to healthcare researchers across research experience levels, aiming to provide insight into GenAI’s role in the research pipeline and their views and experience of the benefits and risks associated with its use. Public perception of GenAI use in healthcare research and perceived impact on healthcare will be investigated. An experimental study will be conducted to assess how healthcare PhD students utilise GenAI to conduct data analysis. This experiment will implement statistical anomalies that, if not caught, impact results and interpretation, assessing whether students are managing these risks properly. This proposed programme of research will provide evidence on how healthcare researchers (including student learners) are implementing GenAI in their workflow, particularly in fields outside their core domain: a poorly understood area of research with impacts to rigor, integrity, interdisciplinary research, and ethical implications. These findings aim to inform an initial framework for utilising GenAI outside one’s core domain, particularly data analytics, effectively informing policy developments on the education and training of future and current healthcare researchers.

UKRI Gateway to Research · FY 2025 · 2025-10

Re-Source is an online marketplace which makes inventory management and resource sharing for theatre companies simple, enjoyable, and sustainable unlike the manual methods of multiple telephone calls and rummaging through sheds which are typical today. 

UKRI Gateway to Research · FY 2025 · 2025-10

Context and Challenge Climate change is reshaping our indoor environments, bringing higher temperatures, shifting humidity levels, and altering pollution patterns in buildings. As we strive for enhanced energy efficiency in buildings to meet the UK Government’s 2050 Net Zero targets, there is a risk of compromising indoor environmental quality (IEQ), particularly due to reduced ventilation when indoor pollution sources are not addressed. While outdoor greening solutions like green walls and trees are well-researched and increasingly in popularity, we lack a clear understanding of how indoor plants affect IEQ and their interplay with outdoor greening near buildings and how their impact will change as the climate warms. GREENIN will address these knowledge gaps by studying key questions about indoor plants and IEQ. The research aims to explore the effectiveness of indoor plants in purifying air, regulating temperature, and controlling humidity, and how building design, construction, and the inhabitants’ activities affect the impact of indoor plants. GREENIN will focus on determining the best ways to measure the potential benefits of indoor greening and examine how climate change might influence these benefits. Additionally, the network will investigate the effects of indoor plants on human health and well-being, while identifying the most effective plants and methods for creating healthier indoor environments. Vision, Aims, and Objectives GREENIN seeks to revolutionise our understanding of indoor green spaces and their impact on health and well-being. To achieve this, our initial, multidisciplinary team - comprising researchers from five leading UK institutions and 27 key stakeholders, including international partners - provides the foundation of the network, which will evolve into a nationally and internationally recognised force in the field. Our objectives are to: (1) Build a network of multidisciplinary specialists; (2) Conduct collaborative studies to expand our knowledge of indoor greening; (3) Create practical guidelines for building design and management professionals; and (4) Promote wider use of greening to enhance building environments and public health. GREENIN will explore the optimal design and implementation of indoor green spaces, assess their advantages and disadvantages under changing environmental conditions, and evaluate their effects on IEQ. Additionally, GREENIN will examine the broader impacts of greening both inside and around buildings, including potential energy savings and heat mitigation. Our goal is to guide informed decisions about improving indoor environmental quality in a warming climate, integrating green features to create healthier, safer indoor environments while addressing energy conservation and climate change challenges. Potential Applications and Benefits GREENIN's research has wide-ranging potential benefits, providing evidence on whether and how indoor plants improve IEQ, and create healthier spaces. This includes studying air quality, hygrothermal control, and biological, social, and psychological effects. Our work will offer practical insights for designing healthier indoor green spaces while supporting energy efficiency and heat reduction. These insights will benefit the public, especially vulnerable populations such as the elderly and those with health conditions sensitive to poor indoor air quality. By involving businesses, policymakers, and environmental groups, GREENIN will help incorporate greening practices into building design and management. Our guidelines, policy advice, and innovative solutions will influence urban and indoor planning, creating healthier indoor environments resilient to climate change challenges.

UKRI Gateway to Research · FY 2025 · 2025-09

The UK acoustics industry directly accounts for over 16,000 jobs and £4.6 billion of GDP and contributes to vibrant growth sectors of the UK economy: communication technologies, consumer electronics, healthcare, and the creative industries. We are witnessing a transformation of this industry through two key technologies — spatial audio and machine learning (ML). Over the past decade, spatial audio has become a cornerstone of media platforms and user experiences, featured in technologies ranging from Dolby Atmos sound on Netflix and Apple AirPods, to second-generation virtual/augmented reality headsets, live music performances, and art installations. More recently, ChatGPT’s media explosion has brought the capabilities of artificial intelligence (AI) into the popular consciousness, heralding the ferocious potential of ML technologies. Despite exciting advancements in audio, acoustics, and AI, a main obstacle is stifling research—scarcity of data resources. This data can take several forms, from audio recordings under various acoustic conditions to human responses to auditory stimuli. Current infrastructure in the UK is not set up to efficiently capture such data, forcing the research community into relying either on large, simulated datasets which may not match real-world conditions, or on real-world datasets that have limited variability in terms of room acoustic conditions. This is problematic because the effectiveness of ML and spatial audio methods hinges on the availability of large (in the case of ML, vast) quantities of high-quality, diverse data collected under realistic acoustic conditions. The alternative, i.e. relocating people and audio equipment to record data in many different locations, is expensive and impractical. Embedded within the established research strengths around spatial sound perception and ML in audio at Surrey, AURORA³ (pronounced “aurora cubed” or simply “aurora”) aims to overcome this data resourcing challenge and establish next-generation strategic infrastructure. AURORA³ will combine state-of-the-art audio equipment and facilities for rigorous, yet precise control over a wide range of acoustic conditions: a variable acoustics room equipped with adjustable wall panels that can transform the acoustics of the room at the push of a button—from church-like reverberance to studio-like dryness—and a moving wall for modifying the room volume; an acoustic anechoic chamber tailored to spatial audio applications, featuring a semi-permanent spherical loudspeaker array for investigating interactions with simulated or recorded environments and soundscapes. Together, these facilities will enable full acoustic environment control for fast, accurate and reproducible physical and perceptual data collection. Technologies developed using AURORA³ will be more robust to different real-world environments and will be able to better model the underlying physical and perceptual phenomena involved in audio and acoustics. This will unlock benefits across a range of applications, including (a) more immersive Virtual/Augmented/Mixed Reality experiences for entertainment, metaverse, remote communications, and virtual prototyping; (b) more accurate and robust consumer electronics devices for automatic speech recognition, speech enhancement and source separation; and (c) smarter hearing aid devices that better understand and adapt to the acoustic scene.

UKRI Gateway to Research · FY 2025 · 2025-09

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

UKRI Gateway to Research · FY 2025 · 2025-09

Atrial fibrillation (AF) affects over 43 million people worldwide, posing serious health risks like stroke, heart attack, heart failure, and death. Current treatments often fail and can have severe side effects, making it crucial to develop safer, more effective therapies. To understand AF better and create new treatments, scientists rely on animal models. However, these models have significant drawbacks. Small animals like rodents differ greatly from humans, and larger animals require complex, ethically challenging procedures. This results in the use of many animals, raising ethical concerns and highlighting the need for alternative methods. Our vision is to replace these animal models with a more accurate and ethical alternative. We propose using atrial cardiomyocytes derived from human induced pluripotent stem cells (atrial hiPSC-CM). These cells, grown in the lab, can provide a more precise representation of human atrial physiology. However, to fully replicate the conditions of AF, these cells need to be structurally and functionally matured. Our project aims to achieve this maturation by developing 3D cell clusters known as spheroids. We will grow these cells in non-adhesive microwells and use techniques such as electrical stimulation and optimised growth medium to enhance maturation. The objectives of our project are: To create and analyse 3D atrial cell clusters (spheroids) and compare their properties to traditional 2D cell cultures. To investigate how electrical stimulation and optimised culture media can enhance the maturity of these cell clusters. To evaluate if these mature cell clusters can accurately model AF when subjected to rapid electrical pacing. The success of this project will provide a more accurate and ethical method for studying AF, significantly reducing the reliance on animal testing. Our approach is simple and utilises standard laboratory equipment, ensuring it can be easily adopted by other research laboratories. Given our extensive preliminary data and the team's solid expertise in this field, we are confident in the project's success.

UKRI Gateway to Research · FY 2025 · 2025-09

As billions of smart devices, such as medical wearables and environmental/industrial sensors, become embedded in everyday life, the need for secure, energy-efficient, and sustainable electronics has become urgent. These devices, fabricated at extremely low cost, must operate reliably and deliver trustworthy data, all while resisting tampering or misuse. Current approaches that combine complex hardware with software-based security algorithms are too resource-intensive to scale across the multitude of simple, yet essential, devices that will be most representative in a world beyond the Internet of Things (IoT). This project explores a radically simpler and more efficient solution. Thin-film transistors have been shown to harness variations in material properties for realising physically unclonable functions (PUFs). Our approach focuses on the newly developed multimodal thin-film transistor (MMT), which uniquely utilizes multiple naturally occurring and independent sources of physical variation. MMTs offer excellent analog and mixed-signal performance, making them ideal for sensing and computation, while the multi-variable PUFs provide a powerful method for generating secure, device-specific identities. Here, we aim to combine core functionality and embedded security within the same ultra-compact, low-power MMT array. The project is led by the early-career researcher who co-invented the MMT, working with an outstanding collaborator and a focused network of expert partners. Through device design, measurement, and analysis, we will establish technical feasibility while identifying key gaps and opportunities for a larger future initiative. From the outset, we will engage with stakeholders to align this work with national priorities such as sustainable electronics, semiconductor resilience, and trusted hardware platforms. We will also explore the broader social, environmental, and industrial impacts. This work lays the foundation for a new class of secure, scalable electronics, enabling application functionality, trust, and sustainability at the physical level.

UKRI Gateway to Research · FY 2025 · 2025-09

Water is fundamental for basic human needs, economic activities (agriculture, industry, business, energy), social well-being, environment, and ecosystem health, with a value of US$58 trillion annually for economic and environmental importance. The future faces grand challenges of water scarcity and water quality. Population growth to 9.8 billion by 2050, urbanisation and industrial growth will escalate water demand. Climate change aggravates water scarcity and pollution caused by flooding and drought events. 2.2 billion people still lacked access to safely managed drinking water services in 2022. The future calls for Water Reuse and Circular Economy approach to save our water resources. However, a key obstacle is the emerging chemical and biological micropollutants (ECBM) in drinking water and wastewater systems, which reduces the water quality for reuse, and the product value of recovered resources. ECBM can be extremely persistent and accumulative, e.g., per- and polyfluoroalkyl substances (PFAS) micro- and nano-plastics, antimicrobials and resistance genes (AMR), which pose significant risks to environmental and public health. The challenges are multi-level: technical, economic, environmental, legal, political and social. Conventional water/wastewater systems are not sufficient in removing ECBM. Water research innovation and implementation can suffer from adverse outcomes due to a lack of systems thinking, learnt from historical examples, e.g., high cost and energy consumption, conflicting the circular economy and net zero agenda. Incidents related to water safety have been increasingly reported in various regions in the UK. The public's increasing demand for better water quality and existing water poverty issues require low-cost, sustainable solutions. We propose “Better Water for All: Re-engineer water engineering for equitable and resilient access to high-quality water for future generations” Network Plus to address these challenges and develop comprehensive and effective frameworks to manage and reduce emerging chemical and biological micropollutants (ECBM) risks in water/wastewater systems. The Network aims to establish a robust cross-disciplinary network comprising various stakeholders, academic researchers, industry experts, policymakers, NGOs, and public community. The Network will co-create frameworks to address the future challenges posed by ECBM. The Network will develop strategic roadmaps for research themes in water engineering, foster collaboration and support technology development of efficient, low-cost, and sustainable technologies. The Network will advocate water and water engineering to the public, attract more investments to water engineering research and enhance societal impact. The Network is expected to generate significant societal, environmental, and economic impacts “for all” with Equality, diversity and inclusivity principles. The Network will provide a hub for communication, collaboration, knowledge exchange and resource sharing. Engaging with policymakers and the public will emphasise our proactive approach to outreach and policy impact. Strengthened partnerships, generation of new data and evidence, and upskilled human resources will leverage and diversify funding/investment to support the whole lifecycle of water engineering innovation. Enhanced public awareness and systems approaches and outputs will impact policy- and regulation-making.

UKRI Gateway to Research · FY 2025 · 2025-09

The accumulation of plastic wastes is a severe environmental challenge. Present estimates suggest that over 380 Mt plastics are produced annually worldwide, only 16% are currently recycled, while 150-200 Mt plastics are accumulated in landfill or leaked to the natural environment. On the other hand, the global demand for carbon-based chemicals and materials is expected to double in the next 10 years to over two billion tons, which we cannot simply still rely on sourcing from fossil fuels. We need to supply these feedstocks from recycling waste materials, such as plastics. However, until now, there remains significant challenge in bridging the gap between waste management and the resource demand for materials and commodity chemicals. The ultimate way to overcome this challenge is to close the loop by recovering the monomer feedstocks from waste, yet such chemical recycling cannot be easily achieved by traditional thermo-chemical processes, due to the poor tolerance to feedstock contamination, low economic value of products and sizable energy input. On this aspect, mechanochemistry, which utilises mechanical energy to initiate chemical reactions, has clear advantages over traditional thermochemical processes. These advantages arise from reactions taking place in a solventless, solid-state environment, with a high tolerance to variation feedstock qualities. Historically, this technique solely relies on supplying enough energy input to overcome the thermodynamic energy threshold of the chemical reactions. Yet plastics are made to last, therefore the polymer chemical bonds are difficult to break. Therefore, capitalising on the team’s strong background on catalysis and polymer processing, through building collaboration with the mechanochemical community in the UK, CirPla will demonstrate for the first time how catalysis + mechanochemistry can transform the plastic recycling and manufacturing sectors. The catalysts will decrease the activation energy of the polymer chain bond breaking, while mechanochemical conditions supply the energy required to drive the depolymerisation reaction. The effectiveness of this process will be demonstrated with a model plastic polyethylene terephthalate (PET, beverage bottles), with the scope of expanding to other plastics, such as polyamides and polycarbonates, in future studies. By collaborating with the world-unique EPSRC-Resonant Acoustic Mixing research facility led by Prof. Tomislav Frišcic in University of Brimingham, CirPla will push the frontier by: 1. Design effective nanoscale catalysts for maximum product yield; 2. Benchmark mechanochemical systems at different scales for up-scaling assessment; and 3. Understand reaction mechanism for further material and catalyst discovery. This research theme aligns with the UKRI’s strategic theme of “building a greener future”, Innovate UK Circular Plastics Network (UKCPN), and Materials and Manufacturing Vision 2050. Aiming to translate the research discovery for impact delivery beyond the project, CirPla is also closely linked with waste management company (Chambers) and the process manufacturing centre of excellence (CPI), for further technology scale-up and validation. When successfully developed, this new process has the potential to transform the plastic value chain and push towards 100% recycling rate. By sourcing the carbon feedstocks from waste stream as fossil fuel alternatives, it will also facilitate the decarbonisation and defossilisation of the chemical sector, thereby contributing towards a climate neutral circular economy.

UKRI Gateway to Research · FY 2025 · 2025-08

Somatic copy number alterations (CNAs), gains or losses of large genomic regions, are widely prevalent in cancers especially those driven by chromosomal instability. CNAs are associated with disease progression and poor patient outcomes, such as copy number gain of oncogene KRAS in pancreatic cancer. Understanding how CNAs evolve over time during the progression from precancerous lesions to malignancy, metastasis, and treatment resistance is important to detect cancer earlier, predict cancer progression, and inform personalized treatment. Despite numerous studies on the patterns and timing of CNAs, few studies have managed to estimate CNA rates in chronological time, which will be addressed by this project. The declining DNA sequencing cost has increased accessibility to multiple samples from individual patients across space and/or time, which allows us to reconstruct evolutionary dynamics of CNA-driven cancer genomes. The latest development and clinical application of liquid biopsy enable minimally invasive genome-wide profiling of CNAs over time in a cost-effective way. Rapid ultra-low coverage copy number profiling of cell-free DNA has been proposed for precision oncology screening. The rise of longitudinal sequencing on patient-derived cell culture is also providing opportunities to monitor cancer evolution, evaluate treatment efficacy, and detect resistant subclones. These (longitudinal) multi-sample data allow the inference of phylogenetic trees, which provide intuitive diagrams and quantitative estimations to suggest hypotheses about evolutionary history. Phylogenetic inference is indispensable in studying species evolution and disease spread. They are increasingly used in studying cancer evolution and offer insights into intra-tumour heterogeneity, metastasis, and therapeutic resistance. We recently published a method, CNETML, to infer CNA-based trees from multiple samples of individual patients using a maximum likelihood approach, which was the first to allow the estimation of constant CNA rates in time from shallow whole genome sequencing data of longitudinal samples. We have applied CNETML to five patients with ovarian cancer to reveal their genomic histories. However, CNA rates are likely to change after certain events such as genome doubling. To allow estimating variable CNA rates in time, we will develop more realistic models of CNA evolution and better phylogenetic inference methods with wider applicability. To link the reconstructed tree with underlying mutational processes and aetiology, we will attach copy number signatures to nodes in the tree. To explore the landscape of CNA evolution, we will apply our methods to publicly available data of multi-region or longitudinal samples from 893 patients across 16 cancer types, including cell culture data. Similar to widely used phylogenetic inference programs in species evolution, our new programs will expand toolboxes for researchers in cancer evolution and promote applications of cancer phylogenetic inference. Our inferences will contribute to personalized therapy and public health. The estimated CNA rates may better distinguish the modes of copy number evolution and approximate chromosome mis-segregation rate, which are predictive of cancer progression or response to therapy. The estimated time of initiating CNAs indicates possible disease onset age, which may suggest potential time windows of screening and surveillance for cancers with unnoticeable early symptoms. The applications of our methods to data across cancer types will uncover similarities and differences in evolutionary trajectories among patients, which will contribute to the discovery of CNA drivers of tumour heterogeneity and patient stratification for personalized treatment. As our methods take CNAs as input, they may be generalized to other diseases featured by CNAs such as neurological disorders.

UKRI Gateway to Research · FY 2025 · 2025-06

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

UKRI Gateway to Research · FY 2025 · 2025-05

Context Fibre-based packaging and bottles are a critical step in reducing the detrimental legacy associated with other packaging materials, which persist in the natural environment and are challenging to recycle. Pulpex Ltd. has in the past four years developed production processes and technologies to deliver sustainable packaging at scale – made from natural wood fibres – that shows promise for liquids in the fast-moving consumer goods sector. The Pulpex bottle uses sustainable materials, can be recycled in existing paper waste-streams, can naturally degrade if not recycled, and has a carbon footprint 30% less than poly(ethylene terephthalate). An essential feature is its multi-layered barrier coating on its interior that prevents the leakage of liquid contents and inward oxygen permeation. However, for Pulpex to design the next generation of production technology and materials, novel and fundamental research (TRL 1-3) is necessary to find missing analytical techniques for product quality improvements, to resolve performance challenges, and to decrease in-process imperfections. Challenges Challenges faced by Pulpex include a need for improved analytical methods to identify imperfections rapidly in barrier coatings on opaque bottles, to ensure product reliability and to minimise wastage. Another challenge is to deliver and automate real-time next generation quality control to adapt materials and manufacturing processes to maximise yield. This is technology that is not commercially available today. Presently, Pulpex technology uses barrier coating materials that are deposited from water and followed with a heating step to drive evaporation and film formation. They now seek next-generation innovative coatings processes that use less energy and water. At the same time, there are continued demands for a longer shelf-life of packaged goods and light weight barriers, which will both only be possible with higher performing barrier systems delivered at scale. Aims and Objectives The aim of this project is to harness a combination of novel coating processes, mechanistic modelling, computer vision, and AI to address the challenges faced in manufacturing sustainable packaging by Pulpex and to underpin the next generation of the process technology. These are not solutions that are commercially available.  The specific objectives are: Develop an alternative “dry” spray coating process to deposit layers that are food-safe and degradable. Investigate the feasibility of using thermal imaging to identify defects in wet coatings as they occur – allowing a quick remedy by drawing on AI. Employ advanced multi-scale mechanistic models of the coatings process to identify ways to optimise it to eliminate all defects and non-uniformities in coatings. Apply new modes of computer vision with AI to identify defects in industrial production and optimise the materials and processing to ensure 100% reliability of the sustainable packaging. Benefits By joining forces with Surrey’s eminent scientists and engineers, Pulpex will see benefits in their technologies and processes. In turn, brand owners of fast-moving consumer goods will have confidence in using their products, which will lead to expanded sales and more jobs at Pulpex’s Cambridgeshire site. Brand owners will be able to meet their Net Zero targets and to comply with Extended Producer Responsibility and UK Plastic Pact regulation, along with any forthcoming legislation arising from the UN Global Plastics Treaty. Consumers will have a greater packaging choice and reduce their personal environmental impact. There will be benefits to the environment from a reduced amount of plastic pollution and lower carbon emissions from packaging manufacturing.

UKRI Gateway to Research · FY 2025 · 2025-04

Globally 70 million deaf people rely on sign language as their primary form of communication. For many deaf people, written languages are their second or third language and they may not be proficient readers. There is no universal sign language and no direct relationship between the sign language of a given country and its spoken language. Sign languages have their own grammars and lexicons and use both manual (hands) and non manual (body and face) articulators combined with the use of space to convey meaning. Sign languages have evolved naturally within deaf communities, and description of the rules that govern them are still an active area of linguistic research. Automatic conversion from a sign language to a spoken language and vice versa is a complex translation problem and one that is currently unsolved, although much of the relevant state of the art originates from the partners in this grant. Speech recognition is now an everyday consumer technology (e.g. Google Assistant, Alexa and Siri). Furthermore, recent developments in Large Language Models (LLMs) such as Generative Pre-trained Transformers (GPT) have led to new levels of AI epitomised by ChatGPT. Automatic approaches to sign language recognition and production are lagging behind and this proposal seeks to redress that balance. Our vision for this Programme Grant is to solve the sign language translation problem. This involves developing the AI and machine learning tools needed to translate between signed and spoken languages - to allow spoken language to be automatically translated into photo-realistic sign language, and video of sign language to be translated into spoken language. To support this aim, the Programme Grant will curate the largest sign language dataset in the world and use the dataset to build a sign language GPT model that can provide the breadth of application to the deaf community equivalent to what LLMs have provided for written/spoken language. In doing so the Programme Grant will also generate tools for data annotation that will be released for use by the wider community. This outcome will greatly enhance communication between deaf and hearing people, enabling full access for deaf people in today's information society. To achieve this we assemble a large multidisciplinary research team across leading authorities in computer vision, sign language linguistics, computational linguistics and machine learning and AI: bringing together the Universities of Surrey, Oxford and UCL alongside leading UK Deaf organizations. We will produce open source toolkits for linguistic use, web based demonstrations for accessible dissemination and run outreach programmes alongside collaborative workshops. Our showcase demonstration will be a fully functioning real time sign language interface to chatGPT allowing a fluent signer to converse naturally with a machine.

UKRI Gateway to Research · FY 2025 · 2025-04

Soil-transmitted helminth (STH), or intestinal worm infections, are a major health burden worldwide, particularly in rural and poor urban areas of low- and middle-income countries, including in Southeast Asia. They infect over 1 billion people worldwide, causing considerable disease including anaemia and stunting and wasting in children. They can also significantly exacerbate poverty, particularly in marginalised communities. In the Philippines nearly 30% of school-aged children are infected with STHs, whereas in Malaysia and Thailand infections are particularly common in indigenous communities, refugees and migrants. The diseases caused by STHs are classified as Neglected Tropical Diseases by the World Health Organization (WHO). In its Roadmap for Neglected Tropical Diseases, WHO targets STH diseases for elimination as a public health problem by 2030. The main approach for STH control is regular distribution of deworming drugs to individuals living in endemic areas. However, there are concerns that resistance will arise to deworming drugs in human STHs, as is common in similar worm infections in animals, thus jeopardising control programmes. Therefore, there is an urgent need to understand how effective deworming drugs are in treating STHs, what the impacts would be on WHO elimination targets if resistance does emerge and explore alternative control approaches. Our project brings together an interdisciplinary team of expert researchers from Malaysia, the Philippines, Thailand and the United Kingdom and aims to address current knowledge gaps in relation to performance of deworming drugs in treatment of STHs and to identify alternative control strategies for STHs which are acceptable to communities. We will do this by undertaking field studies to assess performance of deworming drugs in treatment of STHs in areas of the three countries where high levels of STHs persist despite deworming treatment. We will use cutting edge genomics approaches to determine whether there are genetic variations associated with resistance to deworming treatment in the STHs circulating in the study sites. We will also investigate interactions between STHs and deworming treatment and people’s gut microbial community (microbiome) to propose alternative STH treatment options and to explore if gut microbes might influence treatment responses. Furthermore, we will employ machine learning methods to predict emergence of resistance to deworming drugs and use mathematical modelling and health economics approaches, informed by preference, symptoms and health-related quality-of-life data collected during the field studies, to determine what impact emergence of resistance will have on STH control and identify alternative control approaches which are acceptable to communities. Finally, we will design a strategy to monitor for emergence of deworming resistance. Integrated into the project will be a programme of knowledge exchange and research capacity building activities including training courses, researcher exchanges and field-based training. By embracing a collaborative interdisciplinary approach, this project will shed new light on the issue of STH resistance to deworming drugs and the effect that emergence of resistance will have on STH control and elimination. Ultimately, the project will deliver evidence-based strategies to monitor for resistance emergence and minimise the impact of resistance emergence on achieving the WHO 2030 targets, crucial information for public health policy makers.

UKRI Gateway to Research · FY 2025 · 2025-04

All languages have syllables, but all languages do syllables differently. Syllables are universal building blocks, binding together consonants and vowels into larger units, which can then be formed into words and phrases, and further into speech and song. Yet despite being ubiquitous, syllables possess a structure and complexity varies enormously from language to language. In this Catalyst project I will uncover the processes by which this diversity evolves by developing open-source computational tools for syllable analysis and applying these to a selected dataset of words from 897 languages. Syllables are defined by both their shape and their content. Some languages allow only syllables with a simple shape, consisting of a consonant and a vowel (CV, as in the syllables lo and go in the word logo). Others, such as English and many other European languages, permit more complex shapes, e.g. CVC (as in both syllables of san.dal) or CCV (as in the glo of glory). At the extreme, languages can permit highly complex syllable shapes, forming words without any vowels at all, e.g. Tashlhiyt Berber rgl 'close!'. Languages may also impose different restrictions on the content which can fill these shapes. While English allows a cluster of two consonants at the beginning of the word, not every combination of consonants can occur in this position: a cluster like gl, as in glory, is permissible, but one such as lm, as in Pashto lmundz ‘prayer’, is not. Languages evolve with respect to the types of syllables they allow. Old Church Slavonic migla ‘fog’ and Polish mgla ‘fog’ have the same Common Slavonic origin, but Polish has lost the first vowel, creating an initial cluster /mgw/, which is impossible in Old Church Slavonic. English words like knee and knight used to be pronounced with both /k/ and /n/, but the /k/ sound has been lost and Modern English words cannot begin with the sequence /kn/, unlike in German, where in the corresponding words Knie and Knecht both /k/ and /n/ are pronounced. While syllables can change in a multitude of ways, much remains to be understood about how and why these changes occur. In this project, I will systematically investigate how languages differ in terms of the shape and content of the syllables they allow and model how this changes through time. To do so, I will develop a suite of open-source computational tools for syllable analysis and apply these tools to a specially developed dataset of word forms in a diverse set of languages. First, I will write tools to infer syllable structure from lists of word forms. This will allow me to evaluate syllable structure for many more languages than has hitherto been possible, allowing me to refine existing typologies and to state more clearly the distribution of different syllable types across the languages of the world. Second, I will develop tools to model the evolution of syllable structure through time, so arriving at a more detailed and nuanced understanding of how sound systems diversify and change in human languages.